The proliferation and affordability of smart sensors such aswebcams, microphones etc., has created opportunities for
exciting new classes of distributed services. A key stum-
bling block to mining these rich information sources is the
lack of a common, scalable networked infrastructure for col-
lecting, filtering, and combining the video feeds, extracting
the useful information, and enabling distributed queries.
In this demo, we demonstrate the design and an early
prototype of such an infrastructure, called IRIS (Internet-
scale Resource-Intensive Sensor services). IRIS is a poten-
tially global network of smart sensor nodes, with webcams or
other sensors, and organizing nodes that provide the means
to query recent and historical sensor-based data. IRIS ex-
ploits the fact that high-volume sensor feeds are typically
attached to devices with significant computing power and
storage, and running a standard operating system. Aggres-
sive filtering, smart query routing, and semantic caching are
used to dramatically reduce network bandwidth utilization
and improve query response times, as we will demonstrate.
The service that we demonstrate here is that of a park-
ing space finder. This service utilizes webcams that monitor
parking spaces to answer queries such as the availability of
parking spaces near a user’s destination.